The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
In the current Information Age, users have access to large quantities of data on their local computers and almost limitless quantities of data on the intranets and the worldwide computer network known as the Internet.
In order to find desired information, a user typically uses search engines which are ubiquitous, come in a variety of forms and well known in the art. Some search engines are embedded within a program. They are typically used to find information within a single document that is currently open within the program. Common exemplary document search engines include Microsoft® Notepad Find feature and Microsoft® Outlook® Search feature. On the other hand, a desktop search engine enables users to find information on the local computer. Common exemplary desktop search engines include Microsoft® Windows® XP Search and Mac® OS Finder. A web search engine enables users to find information over the Internet (or an intranet). Common exemplary web search engines include Google®, Bing® and Yahoo®. Some search engines are hybrid, in that, they search both local and remote data source(s).
In order to use a search engine, a user seeking information on a desired topic generally inputs a search query consisting of keyword(s) or phrase(s) relevant to the topic into the search interface of the search engine. If the search is performed across a single document, the search engine typically highlights the matches within the document itself. If the search is performed across multiple documents, the search engine typically displays a report with a prioritized list of links pointing to relevant documents containing the search keywords. Oftentimes, a short summary of text is also included for each result. The summary is that portion or portions of the text in the document that contain the keywords from the search query.
Despite the many capabilities of existing search engines, deficiencies still exist in the art. A typical Internet search by a web search engine finds massive amounts of irrelevant data. It takes considerable amount of time and effort on the part of the user to sift through the results before finding the relatively few web pages that are relevant to his needs.
The reason why search engines return so many irrelevant results is because indexing and searching by keywords themselves is not adequate. For example, it is not possible in existing search engines for a user interested in “India” to specify and restrict the search results to “key/value” pairs such as “Capital/New Delhi”.
Another drawback of existing search engines is that they are useless to a user who doesn't already know the keywords relevant to the topic he is interested in. For example, if a user wants to find movies similar to “Jurassic Park”, searching by the keywords “Jurassic Park” and “similar” is useless as it returns pages about “Jurassic Park” also containing the word “similar”.
Yet another drawback of existing search engines is that they fail to present results in a way that is easy for the user to understand the nature and type of found results.
Systems for searching the Intranets, Extranets, Local Area Networks, individual computers and even single documents also generally suffer from these same drawbacks.
In view of the above drawbacks, there remains a need for an effective method of searching data sources for useful information relating to topics of interest.